Pith Number

pith:BVCI6KLI

pith:2026:BVCI6KLI3J45BE73EKHW6FHLKS

not attested not anchored not stored refs pending

Toward a Scientific Discovery Engine for Weather and Climate Data: A Visual Analytics Workbench for Embedding-Based Exploration

Charlie Becker, David John Gagne, John Clyne, John Schreck, Kirsten J. Mayer, Matt Rehme, Nihanth W. Cherukuru

A visual analytics workbench links embedding spaces of weather data back to physical observations so researchers can identify and retrieve similar meteorological events across large archives.

arxiv:2605.00972 v2 · 2026-05-01 · physics.data-an · cs.AI · cs.CV · cs.IR

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{BVCI6KLI3J45BE73EKHW6FHLKS}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

This enables a discovery workflow in which scientists characterize a phenomenon of interest in a well-understood dataset, identifying its signature in latent space, and then use that signature to probe larger, less-labeled archives or ensembles for similar events.

C2weakest assumption

That visual inspection and metadata linking will reliably allow domain scientists to distinguish physically meaningful structures in the embedding space from preprocessing or bias artifacts without additional quantitative validation.

C3one line summary

A visual analytics workbench enables scientists to explore, query, and verify embedding-based similarity searches on weather and climate data by tracing results back to physical evidence.

Receipt and verification

First computed	2026-07-14T02:22:30.377240Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

0d448f2968da79d093fb228f6f14eb54a353e8ff4c31f32e8f5a09507ee0dc7e

Aliases

arxiv: 2605.00972 · arxiv_version: 2605.00972v2 · doi: 10.48550/arxiv.2605.00972 · pith_short_12: BVCI6KLI3J45 · pith_short_16: BVCI6KLI3J45BE73 · pith_short_8: BVCI6KLI

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/BVCI6KLI3J45BE73EKHW6FHLKS \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 0d448f2968da79d093fb228f6f14eb54a353e8ff4c31f32e8f5a09507ee0dc7e

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "79723bfb28e57b10b654d9f31d42e924d1b9caf8d24bef052a0e3903e28c47a1",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CV",
      "cs.IR"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "physics.data-an",
    "submitted_at": "2026-05-01T17:03:33Z",
    "title_canon_sha256": "add15643f5b761f17aa97206b0bb59a9b2ccc1b64d89b1fc7a0a98deb1d4e8b0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.00972",
    "kind": "arxiv",
    "version": 2
  }
}